Fix weird Mac-specific quote marks

CellProfiler · Apr 16, 2021 · a9fbe5b · a9fbe5b
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Showing 4 changed files with 5 additions and 5 deletions.
diff --git a/ExampleFly/ExampleFly.cppipe b/ExampleFly/ExampleFly.cppipe
@@ -150,7 +150,7 @@ IdentifyPrimaryObjects:[module_num:8|svn_version:'Unknown'|variable_revision_num
     # of deviations:2
     Thresholding method:Otsu
 
-IdentifySecondaryObjects:[module_num:9|svn_version:'Unknown'|variable_revision_number:10|show_window:True|notes:['Identify the cells by using the nuclei as a “seed” region, then growing outwards until stopped by the image threshold or by a neighbor. The Propagation method is used to delineate the boundary between neighboring cells.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
+IdentifySecondaryObjects:[module_num:9|svn_version:'Unknown'|variable_revision_number:10|show_window:True|notes:['Identify the cells by using the nuclei as a "seed" region, then growing outwards until stopped by the image threshold or by a neighbor. The Propagation method is used to delineate the boundary between neighboring cells.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
     Select the input objects:Nuclei
     Name the objects to be identified:Cells
     Select the method to identify the secondary objects:Propagation

diff --git a/ExamplePercentPositive/ExamplePercentPositive.cppipe b/ExamplePercentPositive/ExamplePercentPositive.cppipe
@@ -96,7 +96,7 @@ IdentifyPrimaryObjects:[module_num:5|svn_version:'Unknown'|variable_revision_num
     # of deviations:2.0
     Thresholding method:Otsu
 
-IdentifyPrimaryObjects:[module_num:6|svn_version:'Unknown'|variable_revision_number:14|show_window:True|notes:['The phosphorylated histone probe is a marker for detecting mitotic cells. By segmenting this channel, a threshold is automatically chosen that identifies the pixels that are “positive” for the PH3 probe. This method will yield inconsistent results if there are no mitotic cells in view, so a minimum threshold value is chosen. This minimum is chosen hueristically, based upon the threshold chosen by this module, e.g. half the chosen threshold.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
+IdentifyPrimaryObjects:[module_num:6|svn_version:'Unknown'|variable_revision_number:14|show_window:True|notes:['The phosphorylated histone probe is a marker for detecting mitotic cells. By segmenting this channel, a threshold is automatically chosen that identifies the pixels that are "positive" for the PH3 probe. This method will yield inconsistent results if there are no mitotic cells in view, so a minimum threshold value is chosen. This minimum is chosen hueristically, based upon the threshold chosen by this module, e.g. half the chosen threshold.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
     Select the input image:OrigGreen
     Name the primary objects to be identified:PH3
     Typical diameter of objects, in pixel units (Min,Max):5,20

diff --git a/ExampleVitraImages/ExampleVitra.cppipe b/ExampleVitraImages/ExampleVitra.cppipe
@@ -131,7 +131,7 @@ IdentifyPrimaryObjects:[module_num:6|svn_version:'Unknown'|variable_revision_num
     # of deviations:2
     Thresholding method:Otsu
 
-IdentifySecondaryObjects:[module_num:7|svn_version:'Unknown'|variable_revision_number:10|show_window:True|notes:['Identify the cells by using the nuclei as a “seed” region, then growing outwards until stopped by the image threshold or by a neighbor. The Distance-B method is used to delineate the boundary between neighboring cells.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
+IdentifySecondaryObjects:[module_num:7|svn_version:'Unknown'|variable_revision_number:10|show_window:True|notes:['Identify the cells by using the nuclei as a "seed" region, then growing outwards until stopped by the image threshold or by a neighbor. The Distance-B method is used to delineate the boundary between neighboring cells.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
     Select the input objects:Nuclei
     Name the objects to be identified:Cells
     Select the method to identify the secondary objects:Distance - B

diff --git a/ExampleYeastPatches/ExampleYeastPatches.cppipe b/ExampleYeastPatches/ExampleYeastPatches.cppipe
@@ -94,7 +94,7 @@ ColorToGray:[module_num:6|svn_version:'Unknown'|variable_revision_number:4|show_
     Relative weight of the channel:1.0
     Image name:Channel1
 
-CorrectIlluminationCalculate:[module_num:7|svn_version:'Unknown'|variable_revision_number:2|show_window:True|notes:['The illumination is not uneven and the yeast patches sit on an agar plate that has background signal. The CorrectIlluminationCalculate module will “filter out” the patches and measure the background. The convex hull smoothing method works well with the masked image and reflects the natural contours of uneven illumination.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
+CorrectIlluminationCalculate:[module_num:7|svn_version:'Unknown'|variable_revision_number:2|show_window:True|notes:['The illumination is not uneven and the yeast patches sit on an agar plate that has background signal. The CorrectIlluminationCalculate module will "filter out" the patches and measure the background. The convex hull smoothing method works well with the masked image and reflects the natural contours of uneven illumination.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
     Select the input image:CropGray
     Name the output image:Illumgray
     Select how the illumination function is calculated:Background
@@ -132,7 +132,7 @@ Closing:[module_num:9|svn_version:'Unknown'|variable_revision_number:1|show_wind
     Name the output image:ClosingGray
     Structuring element:disk,5
 
-IdentifyPrimaryObjects:[module_num:10|svn_version:'Unknown'|variable_revision_number:14|show_window:True|notes:['The yeast patches will be segmented, but, despite cropping the image, there will still be plate edges that get segmented, too. Therefore, any object will be referred to as a “pre-spot” that will next be filtered to remove artifactual objects.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
+IdentifyPrimaryObjects:[module_num:10|svn_version:'Unknown'|variable_revision_number:14|show_window:True|notes:['The yeast patches will be segmented, but, despite cropping the image, there will still be plate edges that get segmented, too. Therefore, any object will be referred to as a "pre-spot" that will next be filtered to remove artifactual objects.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
     Select the input image:ClosingGray
     Name the primary objects to be identified:Prespots
     Typical diameter of objects, in pixel units (Min,Max):20,80